IoT Landscape Defies Mapping

SAN JOSE, Calif. -- The landscape of the Internet of Things is more fragmented than the mind of Sybil, the poster child for multiple personality disorder.

Patrick Moorhead recently tried to provide a little therapeutic organization to the mess in a recent Forbes article. Here’s how he broke down IoT from his company-centric viewpoint as a strategy consultant:

IBM Smarter Planet has identified relevant IoT real-world issues for vertical markets and has what looks like a large marketing and consulting effort aimed at vendors in those verticals.

Cisco’s Internet Business Solutions Group is in the Internet of Everything (IoE) camp -- IoT being, apparently, insufficient.

HP M2M Solutions is focused on M2M communications and not yet focused on an integrated IS strategy.

Qualcomm is in the IoE camp and is similarly focused on end-points and M2M communications without including the larger IS picture.

Internet-of-Things Architecture (IoT-A), formed in 2009, is a European Lighthouse Integrated Project that gets good marks on completeness of vision and being forward looking.

That’s not a bad starting point, but it misses a lot of activities humming deeper in the technical weeds like so many crickets. Here I would point to more dev kits than you can shake a stick at. To name just a few representative examples, they include:

I credit Dust Networks with being one of the pioneers of the field. The startup spun out of a Berkeley research project is now part of Linear Technology. Dust is just one high-profile example of a whole set of leaders from that era, some of which have not survived.

Another way to track this fragmented landscape is via actual deployments. But this is the most murky part of the IoT territory.

Many deployments are embedded deep into SCADA infrastructure projects that are not widely publicized and probably don’t want to be, for security reasons. They range from city traffic cams to farm irrigation systems. And let’s not forget the emerging market for wearable computers.

I am keen to map out this piece of the terrain because it holds the promise of best-practices and lessons learned -- quite a promising harvest.

>> The idea was that the ISP could trace the origin of data flows to enable them to charge Netflix, Google, etc. based on how much data they originated in addition to charging their customers to access those flows

That will be the battle of the next decade. The way my internet connection slows down when the college kid that stays closer by returns to when he is gone demonstrates that Netflix and co may have to support the pipes that keep them in business. If they do not and the network owners refuse to innovate, their business model will be in jeopardy.

It seems to me that part of the problem with IoT at this early stage is that the concept is not totally defined. I still think IoT means different things to different people. It's early days for IoT, but there is a lot of work needed in standardizing on technologies.

While reading your post I flashed back to the late '80s and early '90s when I was explaining to confused executives what this new "Internet" thingie was and what it meant to their businesses. This iteration is even more far-reaching, but the basic principles of distributed sensing and computation apply. IoT is in one respect an advancing wave of connected sensors and smart devices, but it is also an incremental expansion of the Internet. Rather than replacing what has gone before it will force it to evolve. Big data analysis will need to be able to handle truly massive amounts of data in real time. Networks will need to handle cross-flows peer to peer and outside-in data flows as effectively as they currently handle data flows that are primarily from servers to the edge of the network.

Business model changes are going to be interesting to watch as well. I heard a network equipment exec at one conference talking about how they were enabling an ISP business model that he referred to, without any trace of irony, as being a "Two-faced business model". The idea was that the ISP could trace the origin of data flows to enable them to charge Netflix, Google, etc. based on how much data they originated in addition to charging their customers to access those flows. How does this change when Google is aggregating data flows from millions of sensors?

It is true that the term IoT englobes many technologies and interpretations. In a way it reflects the exciting realm of possibilities we now have. I worry about security issues to be honest and I think many are under-estimating this real problem.

When you envision IoT futures, those "things" must be connected somehow to the other hot topic, Big Data, the cloud-based analytics that generate the contextual smarts for new ambient and wearable systems. But the connective infrastructure is often left out of the discussion.

We didn't miss these other activites, we deliberately side-stepped them to focus a portion of the discussion on larger organizations and companies who are taking the first steps toward building the pervasive connective infrastructure that affordable services will depend on to enable smaller, more power efficient wearable and embedded tech to be smarter than their power and price budgets would otherwise allow.

Please click through Pat's article to our paper. And then let's talk about mapping out the large scale features of an ambient computing future. End-to-end solutions must have a middle... ;v)

The claim for being first with networked embedded control devices helongs to Echelon [http://www.echelon.com/company/] - dating some 20 years. Efforts to assimilate embedded devices into the Internet are futile! :-) [as the market fragmentation demonstrations.]